This study focuses on learning with the Global Change app, an interactive tool for fostering climate change knowledge. Numerous studies have contributed to the question on what type of instruction is best to achieve learning gains. The findings are mixed. We applied the app in university courses and investigated which instructional setting a discovery learning approach (no supplementary guidance) or an approach that leans more toward direct instruction is more effective (+ supplementary guidance). Thus, we distinguished between conceptual and procedural guidance within our direct instruction approach. Our study was implemented in a digital learning environment with 110 students participating in the study. We applied a 2 × 2 experimental design with different types of guidance as treatment (conceptual and procedural). An online questionnaire was administered in pretest and posttest to measure climate change knowledge as well as different variables. Our results show that the app provided gains in climate change knowledge in a short period of time regardless of treatment. Further, students who received no supplementary guidance acquired more knowledge about climate change than the groups that received supplemental guidance (either conceptual, procedural, or both). Learning gain correlated significantly negatively with cognitive load across the whole sample, but there were no significant differences between groups. This finding might be interpreted in terms of the renowned expertise reversal effect.
ZusammenfassungWelchen Wert haben Tiere? Wie sollten Menschen mit Tieren in der Landwirtschaft umgehen? Zur Beantwortung dieser Fragen müssen Lernende ethisch argumentieren und biologisches, philosophisches oder theologisches Wissen heranziehen. Deshalb werden Vorstellungen von Lernenden und Schulbuchinhalte zu diesen tierethischen Problemfeldern verglichen und auf Lernchancen und -hürden überprüft. Anschließend werden didaktische Empfehlungen daraus abgeleitet. In den Moralvorstellungen der Lernenden wurden zahlreiche Moralmetaphern identifiziert, welche Rückschlüsse auf die Gestaltung von interdisziplinären Lernumgebungen erlauben.
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